Estimating Sensitivity and Sojourn Time in Screening for Colorectal Cancer A Comparison of Statistical Approaches
TL;DR: Various analytic strategies for fitting exponential models to data from a screening program for colorectal cancer conducted in Calvados, France, between 1991 and 1994 are considered, yielding estimates of mean sojourn time and sensitivity.
Abstract: The effectiveness of cancer screening depends crucially on two elements: the sojourn time (that is, the duration of the preclinical screen-detectable period) and the sensitivity of the screening test. Previous literature on methods of estimating mean sojourn time and sensitivity has largely concentrated on breast cancer screening. Screening for colorectal cancer has been shown to be effective in randomized trials, but there is little literature on the estimation of sojourn time and sensitivity. It would be interesting to demonstrate whether methods commonly used in breast cancer screening could be used in colorectal cancer screening. In this paper, the authors consider various analytic strategies for fitting exponential models to data from a screening program for colorectal cancer conducted in Calvados, France, between 1991 and 1994. The models yielded estimates of mean sojourn time of approximately 2 years for 45- to 54-year-olds, 3 years for 55- to 64-year-olds, and 6 years for 65- to 74-year-olds. Estimates of sensitivity were approximately 75%, 50%, and 40% for persons aged 45-54, 55-64, and 65-74 years, respectively. There is room for improvement in all models in terms of goodness of fit, particularly for the first year after screening, but results from randomized trials indicate that the sensitivity estimates are roughly correct. Am J Epidemiol 1998;148:609-19.
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TL;DR: Findings support the hypothesis that colonoscopic removal of adenomatous polyps prevents death from colorectal cancer.
Abstract: BACKGROUND In the National Polyp Study (NPS), colorectal cancer was prevented by colonoscopic removal of adenomatous polyps. We evaluated the long-term effect of colonoscopic polypectomy in a study on mortality from colorectal cancer. METHODS We included in this analysis all patients prospectively referred for initial colonoscopy (between 1980 and 1990) at NPS clinical centers who had polyps (adenomas and nonadenomas). The National Death Index was used to identify deaths and to determine the cause of death; follow-up time was as long as 23 years. Mortality from colorectal cancer among patients with adenomas removed was compared with the expected incidence-based mortality from colorectal cancer in the general population, as estimated from the Surveillance Epidemiology and End Results (SEER) Program, and with the observed mortality from colorectal cancer among patients with nonadenomatous polyps (internal control group). RESULTS Among 2602 patients who had adenomas removed during participation in the study, after a median of 15.8 years, 1246 patients had died from any cause and 12 had died from colorectal cancer. Given an estimated 25.4 expected deaths from colorectal cancer in the general population, the standardized incidence-based mortality ratio was 0.47 (95% confidence interval [CI], 0.26 to 0.80) with colonoscopic polypectomy, suggesting a 53% reduction in mortality. Mortality from colorectal cancer was similar among patients with adenomas and those with nonadenomatous polyps during the first 10 years after polypectomy (relative risk, 1.2; 95% CI, 0.1 to 10.6). CONCLUSIONS These findings support the hypothesis that colonoscopic removal of adenomatous polyps prevents death from colorectal cancer. (Funded by the National Cancer Institute and others.)
2,381 citations
TL;DR: A framework to guide individualized cancer screening decisions in older patients may be more useful to the practicing clinician than age guidelines because it anchors decisions through quantitative estimates of life expectancy, risk of cancer death, and screening outcomes based on published data.
Abstract: Considerable uncertainty exists about the use of cancer screening tests in older people, as illustrated by the different age cutoffs recommended by various guideline panels. We suggest that a framework to guide individualized cancer screening decisions in older patients may be more useful to the practicing clinician than age guidelines. Like many medical decisions, cancer screening decisions require weighing quantitative information, such as risk of cancer death and likelihood of beneficial and adverse screening outcomes, as well as qualitative factors, such as individual patients' values and preferences. Our framework first anchors decisions through quantitative estimates of life expectancy, risk of cancer death, and screening outcomes based on published data. Potential benefits of screening are presented as the number needed to screen to prevent 1 cancer-specific death, based on the estimated life expectancy during which a patient will be screened. Estimates reveal substantial variability in the likelihood of benefit for patients of similar ages with varying life expectancies. In fact, patients with life expectancies of less than 5 years are unlikely to derive any survival benefit from cancer screening. We also consider the likelihood of potential harm from screening according to patient factors and test characteristics. Some of the greatest harms of screening occur by detecting cancers that would never have become clinically significant. This becomes more likely as life expectancy decreases. Finally, since many cancer screening decisions in older adults cannot be answered solely by quantitative estimates of benefits and harms, considering the estimated outcomes according to the patient's own values and preferences is the final step for making informed screening decisions.
955 citations
TL;DR: Screening data with tumor measurements can provide population-based estimates of tumor growth and screen test sensitivity directly linked to tumor size, and there is a large variation in breast cancer tumor growth, with faster growth among younger women.
Abstract: Knowledge of tumor growth is important in the planning and evaluation of screening programs, clinical trials, and epidemiological studies. Studies of tumor growth rates in humans are usually based on small and selected samples. In the present study based on the Norwegian Breast Cancer Screening Program, tumor growth was estimated from a large population using a new estimating procedure/model. A likelihood-based estimating procedure was used, where both tumor growth and the screen test sensitivity were modeled as continuously increasing functions of tumor size. The method was applied to cancer incidence and tumor measurement data from 395,188 women aged 50 to 69 years. Tumor growth varied considerably between subjects, with 5% of tumors taking less than 1.2 months to grow from 10 mm to 20 mm in diameter, and another 5% taking more than 6.3 years. The mean time a tumor needed to grow from 10 mm to 20 mm in diameter was estimated as 1.7 years, increasing with age. The screen test sensitivity was estimated to increase sharply with tumor size, rising from 26% at 5 mm to 91% at 10 mm. Compared with previously used Markov models for tumor progression, the applied model gave considerably higher model fit (85% increased predictive power) and provided estimates directly linked to tumor size. Screening data with tumor measurements can provide population-based estimates of tumor growth and screen test sensitivity directly linked to tumor size. There is a large variation in breast cancer tumor growth, with faster growth among younger women.
179 citations
Cites background or methods or result from "Estimating Sensitivity and Sojourn ..."
...To make the results comparable with estimates provided in previous studies [5,12-15], all cases of ductal carcinoma in situ (DCIS) – a noninvasive form of breast tumor – were included....
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...time unit (month) without screening – to simplify calculations, the rate is assumed constant over time as in the earlier used Markov model [5,12], probably giving a good approximation in the limited time span used in the estimation – and , i f gs , is the probability that a clinical...
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...Overall, sensitivity investigations indicate that the new model is probably less vulnerable to several potential biases than the Markov model [5,12], possibly as a result of more utilized data....
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...Generally, this model combines many of the advantages of the large population-based Markov methods [5,12], with more specific tumor growth estimates found in clinical studies of overlooked cancers....
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...These studies [1] are usually analyzed using Markov models [5,6], where the mean time for a breast cancer tumor to growth from screening-detectable size to clinical detection without screening – the so-called mean sojourn time – and the STS are estimated....
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TL;DR: Lead-time bias is the main determinant of the short-term benefit provided by surveillance for HCC, but this benefit becomes factual in a long-term perspective, confirming the clinical utility of an anticipated diagnosis of HCC.
109 citations
Cites methods from "Estimating Sensitivity and Sojourn ..."
...This study was aimed at accurately estimating the lead time affecting semiannual and annual surveillance for HCC through a rigorous mathematical model already proposed in other cancer screening programs [15-16]....
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...This distribution was used to calculate the transition rate to symptomatic disease and lead time, using the appropriate formula (equation 4) [15,16,19]....
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TL;DR: Dietary patterns that reflect a Western way of life are associated with a higher risk of colorectal tumors.
Abstract: Little is known about the dietary patterns associated with colorectal tumors along the adenoma-carcinoma sequence. Scores for dietary patterns were obtained by factor analysis in women from the French cohort of the European Prospective Investigation into Cancer and Nutrition (1993-2000). Their association with colorectal tumors was investigated in 516 adenoma cases (175 high-risk adenomas) and 4,804 polyp-free women and in 172 colorectal cancer cases and 67,312 cancer-free women. The authors identified four dietary patterns: "healthy" (vegetables, fruit, yogurt, sea products, and olive oil); "Western" (potatoes, pizzas and pies, sandwiches, sweets, cakes, cheese, cereal products, processed meat, eggs, and butter); "drinker" (sandwiches, snacks, processed meat, and alcoholic beverages); and "meat eaters" (meat, poultry, and margarine). For quartile 4 versus quartile 1, an increased risk of adenoma was observed with high scores of the Western pattern (multivariate relative risk (RR) = 1.39, 95% confidence interval: 1.00, 1.94; p(trend) = 0.03) and the drinker pattern (RR = 1.42, 95% confidence interval: 1.10, 1.83; p(trend) = 0.01). The meat-eaters pattern was positively associated with colorectal cancer risk (for quartile 4 vs. quartile 1: RR = 1.58, 95% confidence interval: 0.98, 2.53; p(trend) = 0.02). Dietary patterns that reflect a Western way of life are associated with a higher risk of colorectal tumors.
106 citations
References
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TL;DR: The purpose of this paper is to discuss statistical considerations associated with the evaluation of such early detection programmes, and to examine problems associated with screening programmes where an individual is examined periodically.
Abstract: SIUMMARY It is assumed that a chronic disease progresses from a pre-clinical state to a clinical state. If an individual, having pre-clinical disease, participates in an early detection programme, the disease may be detected in the pre-clinical state. The potential benefit of a screening programme is related to the lead time gained by early diagnosis. A stochastic model is developed for early detection programmes which leads to an estimate of the mean lead time as a function of observable variables. An investigation is also made of a non-progressive disease model in which individuals in a pre-clinical state may not necessarily advance to the clinical state. At the present time special diagnostic procedures are available for early detection of some chronic diseases. For example, chest X-rays have long been used to detect tuberculosis. Currently, there are many public health programmes to detect women having cancer of the uterine cervix by using Papanicolaou smears; other programmes designed to test for glaucoma and diabetes are in wide use. An especially interesting programme for early detection of breast cancer using soft tissue X-rays, mammography, is now being conducted by the Health Insurance Plan of Greater New York; see Shapiro, Strax & Venet (1967). The aim of all such programmes is to detect the disease earlier than it normally would be detected, the motivation being that earlier detection may result in a cure or better prognosis. Unfortunately, with only a few exceptions we know of no chronic disease in which unambiguous evidence has been coLlected showing that early detection has resulted in significantly improved prognosis. Even in cancer of the uterine cervix, the results are not without question, because the survival rate had been increasing before the widespread introduction of the Papanicolaou smear. It is the purpose of this paper to discuss statistical considerations associated with the evaluation of such early detection programmes. Attention is confined to screening programmes where an individual is examined only once. In a future paper, we shall examine problems associated with screening programmes where an individual is examined periodically. It will be assumed that a person having a particular chronic disease can be regarded as
394 citations
TL;DR: The methods are applied to published data from the HIP breast cancer screening project, to which a negative exponential distribution for the sojourn-time distribution fitted better than the other families of distribution considered.
Abstract: The performance of a screening programme depends on a number of parameters, which may need different types of information for their estimation. In this paper, two characteristics of interest, the sojourn-time distribution and the sensitivity, are considered, and estimation procedures, based on data which should be available from a mass screening programme, are proposed. The methods are applied to published data from the HIP breast cancer screening project, to which a negative exponential distribution for the sojourn-time distribution fitted better than the other families of distribution considered.
262 citations
TL;DR: A two-parameter Markov chain model is proposed and developed to explicitly estimate the preclinical incidence rate and the rate of transition from preclinical to clinical state without using control data, and a new estimate of sensitivity is proposed, based on the estimated parameters of the Markov process.
Abstract: The sojourn time, time spent in the preclinical detectable phase (PCDP) for chronic diseases, for example, breast cancer, plays an important role in the design and assessment of screening programmes. Traditional methods to estimate it usually assume a uniform incidence rate of preclinical disease from a randomized control group or historical data. In this paper, a two-parameter Markov chain model is proposed and developed to explicitly estimate the preclinical incidence rate (λ1) and the rate of transition from preclinical to clinical state (λ2, equivalent to the inverse of mean sojourn time) without using control data. A new estimate of sensitivity is proposed, based on the estimated parameters of the Markov process. When this method is applied to the data from the Swedish two-county study of breast cancer screening in the age group 70–74, the estimate of MST is 2·3 with 95 per cent CI ranging from 2·1 to 2·5, which is close to the result based on the traditional method but the 95 per cent CI is narrower using the Markov model. The reason for the greater precision of the latter is the fuller use of all temporal data, since the continuous exact times to events are used in our method instead of grouping them as in the traditional method. Ongoing and future researches should extend this model to include, for example, the tumour size, nodal status and malignancy grade, along with methods of simultaneously estimating sensitivity and the transition rates in the Markov process.
197 citations
TL;DR: The analysis indicates that for screening people over 40 yr old an annual fecal occult blood test may reduce colorectal cancer mortality by about one-third, and the lower cost of the barium enema makes it a more cost-effective strategy.
195 citations
TL;DR: The findings about progression and duration of pre-invasive lesions do not support the still prevailing tendency of frequently making Pap smears in young women.
Abstract: Data from the screening programme in British Columbia are used to test hypotheses about the natural history of cervical cancer, especially about progression and regression of preclinical lesions (dysplasia and carcinoma in situ). Three models are considered. A model without regression does not give an adequate fit of the data (P less than 0.001), and results in an implausible estimate of 33 years for the mean duration of pre-invasive lesions. A model with an equal regression rate at all ages still does not result in a good reproduction of the data. A good fit is achieved for a model with different regression rates in lesions that develop under and over age 34. Under age 34, 84% of the new lesions will regress spontaneously, with a 95% confidence interval of 76-92% regression. Over age 34, we estimate that 40% of the new lesions will regress. The average duration of dysplasia + CIS is 11.8 years, and the sensitivity of the Pap-smear is 80%. It is concluded that a considerable proportion of pre-invasive lesions in young women do not progress. The findings about progression and duration of pre-invasive lesions do not support the still prevailing tendency of frequently making Pap smears in young women.
174 citations